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02/21/2023
Characterizing the Optimal 0-1 Loss for Multi-class Classification with a Test-time Attacker
Finding classifiers robust to adversarial examples is critical for their...
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02/08/2023
GLAZE: Protecting Artists from Style Mimicry by Text-to-Image Models
Recent text-to-image diffusion models such as MidJourney and Stable Diff...
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08/29/2022
Data Isotopes for Data Provenance in DNNs
Today, creators of data-hungry deep neural networks (DNNs) scour the Int...
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06/21/2022
Natural Backdoor Datasets
Extensive literature on backdoor poison attacks has studied attacks and ...
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06/08/2022
Can Backdoor Attacks Survive Time-Varying Models?
Backdoors are powerful attacks against deep neural networks (DNNs). By p...
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05/21/2022
Post-breach Recovery: Protection against White-box Adversarial Examples for Leaked DNN Models
Server breaches are an unfortunate reality on today's Internet. In the c...
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02/11/2022
Assessing Privacy Risks from Feature Vector Reconstruction Attacks
In deep neural networks for facial recognition, feature vectors are nume...
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12/08/2021
SoK: Anti-Facial Recognition Technology
The rapid adoption of facial recognition (FR) technology by both governm...
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10/13/2021
Traceback of Data Poisoning Attacks in Neural Networks
In adversarial machine learning, new defenses against attacks on deep le...
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09/20/2021
"Hello, It's Me": Deep Learning-based Speech Synthesis Attacks in the Real World
Advances in deep learning have introduced a new wave of voice synthesis ...
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05/18/2021
Towards Performance Clarity of Edge Video Analytics
Edge video analytics is becoming the solution to many safety and managem...
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02/08/2021
A Real-time Defense against Website Fingerprinting Attacks
Anonymity systems like Tor are vulnerable to Website Fingerprinting (WF)...
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06/25/2020
Backdoor Attacks on Facial Recognition in the Physical World
Backdoor attacks embed hidden malicious behaviors inside deep neural net...
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06/24/2020
Blacklight: Defending Black-Box Adversarial Attacks on Deep Neural Networks
The vulnerability of deep neural networks (DNNs) to adversarial examples...
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02/19/2020
Fawkes: Protecting Personal Privacy against Unauthorized Deep Learning Models
Today's proliferation of powerful facial recognition models poses a real...
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12/03/2019
Trimming Mobile Applications for Bandwidth-Challenged Networks in Developing Regions
Despite continuous efforts to build and update network infrastructure, m...
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12/03/2019
"How do urban incidents affect traffic speed?" A Deep Graph Convolutional Network for Incident-driven Traffic Speed Prediction
Accurate traffic speed prediction is an important and challenging topic ...
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10/02/2019
Persistent and Unforgeable Watermarks for Deep Neural Networks
As deep learning classifiers continue to mature, model providers with su...
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05/24/2019
Regula Sub-rosa: Latent Backdoor Attacks on Deep Neural Networks
Recent work has proposed the concept of backdoor attacks on deep neural ...
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04/18/2019
Gotta Catch 'Em All: Using Concealed Trapdoors to Detect Adversarial Attacks on Neural Networks
Deep neural networks are vulnerable to adversarial attacks. Numerous eff...
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04/17/2019
Understanding the Effectiveness of Ultrasonic Microphone Jammer
Recent works have explained the principle of using ultrasonic transmissi...
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10/24/2018
Wireless Side-Lobe Eavesdropping Attacks
Millimeter-wave wireless networks offer high throughput and can (ideally...
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10/23/2018
Adversarial WiFi Sensing using a Single Smartphone
Wireless devices are everywhere, at home, at the office, and on the stre...
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10/23/2018
Adversarial WiFi Sensing
Wireless devices are everywhere, at home, at the office, and on the stre...
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09/22/2018
